Testing for similarity in area-based spatial patterns: A nonparametric Monte Carlo approach

Abstract

The proliferation of geographic information systems and point data has made the analysis of spatial point patterns of increasing interest in a variety of disciplines. Though early forms of spatial point pattern analysis were limited in their scope, current forms have been developed that provide significant insight into underlying data generating processes. This paper builds on the spatial point pattern analysis literature through the development of a nonparametric Monte Carlo spatial point pattern test (and corresponding index) to measure the degree of similarity between two spatial point patterns. The applicability of this new test is then shown using crime data.